Analysis Quickstart

If you have not installed Docent yet, start with Installation and run uvx docent@latest setup to configure the SDK, coding-agent plugin, and API key.

Paste one of these prompts into your coding agent to analyze our sample Terminal-Bench collection.

Failure modes
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Collection Overview

/docent What are the main reasons why GPT-5.1 Codex fails?

Identify runs where GPT-5.1 failed. Summarize the primary failure modes in those runs and explain why you think they were decisive. Cluster common failure modes or failing strategies across all runs. Continue to cluster within clusters until you reach failures that are prevalent (i.e. common in the data) and specific (i.e. it is evident to a developer what a concrete fix would look like).

- Collection ID: 479b7093-5a33-47f1-8d7b-fc9f6f16bb75

/docent What are the main reasons why GPT-5.1 Codex underperforms GPT-5 Codex?

Identify tasks where GPT-5.1 regresses on average. On those tasks, compare a failed GPT-5.1 run against the successful GPT-5 runs. Summarize the main failure modes and analyze whether avoiding those failures was material to the result of the successful runs.

- Collection ID: 479b7093-5a33-47f1-8d7b-fc9f6f16bb75

/docent Give me an overview of this collection.

- Collection ID: 479b7093-5a33-47f1-8d7b-fc9f6f16bb75

To analyze your own data instead, swap in the collection ID from the top left corner of your collection, next to the collection name.

Turn on your coding agent’s auto-approval mode so it can generate and run scripts without stopping at each permission prompt — see Claude Code Auto mode or Codex Auto-review. Analysis plan approval is separate, and is controlled in Docent under Settings → Preferences.

Next steps

Ingest your own data

Ready to analyze your own agent runs? Follow the ingestion guide to load your logs into Docent.

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Analysis Quickstart

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Read more about Analysis Plans

Ingest your own data

​Next steps

Read more about Analysis Plans

Ingest your own data

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